{"url":"/dataset/iam-line-level","name":"IAM(line-level)","full_name":"Line-level Handwritten Text Recognition on IAM","description_markdown":"The **IAM** database contains 13,353 images of handwritten lines of text created by 657 writers. The texts those writers transcribed are from the Lancaster-Oslo/Bergen Corpus of British English. It includes contributions from 657 writers making a total of 1,539 handwritten pages comprising of 115,320 words and is categorized as part of modern collection. The database is labeled at the sentence, line, and word levels.\r\n\r\nSource: [Measuring Human Perception to Improve Handwritten Document Transcription](https://arxiv.org/abs/1904.03734)\r\nImage Source: [https://fki.tic.heia-fr.ch/databases/iam-handwriting-database](https://fki.tic.heia-fr.ch/databases/iam-handwriting-database)","description_withheld":null,"homepage":"https://fki.tic.heia-fr.ch/databases/iam-handwriting-database","introduced_date":"2018-02-20","introduced_date_note":null,"introduced_by":null,"license":{"name":"Custom (research-only, non-commercial, attribution)","url":"https://fki.tic.heia-fr.ch/databases/iam-handwriting-database#:~:text=Terms%20of%20Use"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Handwritten Text Recognition","url":"/task/handwritten-text-recognition","datasets_with_task":"/datasets/task/handwritten-text-recognition"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["IAM(line-level)"],"data_loaders":[{"repo":"https://github.com/pythonlessons/mltu","url":"https://fki.tic.heia-fr.ch/DBs/iamDB/data/ascii.tgz","frameworks":["tf"]}],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/handwritten-text-recognition-on-iam-line","task":"Handwritten Text Recognition","dataset_variant":"IAM(line-level)","rows":5,"metrics":["Test CER","Test WER"],"first_row_in_archive_order":{"model":"TrOCR","paper":"/paper/trocr-transformer-based-optical-character","metrics":{"Test CER":"3.4","Test WER":"-"},"code_links":[{"title":"huggingface/transformers","url":"https://github.com/huggingface/transformers"},{"title":"microsoft/unilm","url":"https://github.com/microsoft/unilm/tree/master/trocr"},{"title":"oleehyo/texteller","url":"https://github.com/oleehyo/texteller"},{"title":"d-gurgurov/im2latex","url":"https://github.com/d-gurgurov/im2latex"},{"title":"prathameshza/TrOCR_FineTuning","url":"https://github.com/prathameshza/TrOCR_FineTuning"},{"title":"MindCode-4/code-5","url":"https://github.com/MindCode-4/code-5/tree/main/trocr"},{"title":"pwc-1/Paper-9","url":"https://github.com/pwc-1/Paper-9/tree/main/1/trocr"},{"title":"pwc-1/Paper-10","url":"https://github.com/pwc-1/Paper-10/tree/main/trocr"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/htr-vt-handwritten-text-recognition-with","title":"HTR-VT: Handwritten Text Recognition with Vision Transformer","date":"2024-09-13","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/trocr-transformer-based-optical-character","title":"TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models","date":"2021-09-21","rows_on_this_dataset":1,"code_links":8,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/recurrence-free-unconstrained-handwritten","title":"Recurrence-free unconstrained handwritten text recognition using gated fully convolutional network","date":"2020-12-09","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/end-to-end-handwritten-paragraph-text","title":"End-to-end Handwritten Paragraph Text Recognition Using a Vertical Attention Network","date":"2020-12-07","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/origaminet-weakly-supervised-segmentation-1","title":"OrigamiNet: Weakly-Supervised, Segmentation-Free, One-Step, Full Page Text Recognition by learning to unfold","date":"2020-06-12","rows_on_this_dataset":1,"code_links":8,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":1,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}